Cell Culture Models for the Investigation of Hepatitis B and D Virus Infection
Bibliographic record
Abstract
Chronic hepatitis B virus (HBV) and hepatitis D virus (HDV) infections are major causes of liver disease and hepatocellular carcinoma worldwide. Despite the presence of an efficient preventive vaccine, more than 250 million patients are chronically infected with HBV. Current antivirals effectively control but only rarely cure chronic infection. While the molecular biology of the two viruses has been characterized in great detail, the absence of robust cell culture models for HBV and/or HDV infection has limited the investigation of virus-host interactions. Native hepatoma cell lines do not allow viral infection, and the culture of primary hepatocytes, the natural host cell for the viruses, implies a series of constraints restricting the possibilities of analyzing virus-host interactions. Recently, the discovery of the sodium taurocholate co-transporting polypeptide (NTCP) as a key HBV/HDV cell entry factor has opened the door to a new era of investigation, as NTCP-overexpressing hepatoma cells acquire susceptibility to HBV and HDV infections. In this review, we summarize the major cell culture models for HBV and HDV infection, discuss their advantages and limitations and highlight perspectives for future developments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".